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法国国家信息与自动化研究所脑成像和人口研究图像处理技术博士后职位
文章来源:知识人网整理       更新时间:2020年09月25日

法国国家信息与自动化研究所脑成像和人口研究图像处理技术博士后职位

POST-DOCTORAL RESEARCH VISIT F/M POST-DOCTORAL POPULATION IMAGING WITH NILEARN

INRIA

Job Description

2020-03036 - Post-Doctoral Research Visit F/M Post-doctoral Population imaging with Nilearn

Contract type : Fixed-term contract

Renewable contract : Oui

Level of qualifications required : PhD or equivalent

Fonction : Post-Doctoral Research Visit

About the research centre or Inria department

Located at the heart of the main national research and higher education cluster, member of the Université Paris Saclay, a major actor in the French Investments for the Future Programme (Idex, LabEx, IRT, Equipex) and partner of the main establishments present on the plateau, the centre is particularly active in three major areas: data and knowledge; safety, security and reliability; modelling, simulation and optimisation (with priority given to energy).

The 450 researchers and engineers from Inria and its partners who work in the research centre's 28 teams, the 60 research support staff members, the high- level equipment at their disposal (image walls, high-performance computing clusters, sensor networks), and the privileged relationships with prestigious industrial partners, all make Inria Saclay Île-de-France a key research centre in the local landscape and one that is oriented towards Europe and the world.

Context

Context: the advent of large-scale datasets such as UKBiobank is changing the way we perform population imaging. Sample-rich data (40k subjects with brain imaging, still increasing, 500k with behavioral data) make it possible to improve inference models in an unprecedented way and calls for new approaches. The reliance on imaging-derived phenotype (IDPs) as imposed itself as a key step to scale the analysis. However this can lead to suboptimal inference, because the choices of the IDPs has not be discussed in depth by the community. In this project, we want to build improved IDPs for UKBB, leveraging the techniques build at parietal: signal extraction from optimized atlases, Riemannian representation of the connectivity structure (so-called tangent embedding approach).

Assignment

The post-doc candidate will carry out some data processing tasks on UKBB to extract IDPs on the latest data and provide a more complete collection of data. He or she will also complete the data available on the Parietal server. If significant differences are found with respect to standard IDPs, this will be subject to a publication.

In parallel, the candidate will improve the Nilearn (nilearn.github.io) library that supports all the underlying computation. In particular integration of second- and first-level analysis and BIDS integration. This is expected to facilitate and improve future large-scale analysis for future.

Skills

Development in Python

Knowledge of the field of brain imaging and population studies

Image processing capabilities.

Benefits package

  Subsidized meals

  Partial reimbursement of public transport costs

  Leave: 7 weeks of annual leave + 10 extra days off due to RTT (statutory reduction in working hours) + possibility of exceptional leave (sick children, moving home, etc.)

  Possibility of teleworking (after 6 months of employment) and flexible organization of working hours

  Professional equipment available (videoconferencing, loan of computer equipment, etc.)

  Social, cultural and sports events and activities

  Access to vocational training

  Social security coverageRemuneration

Monthly gross salary : 2.653 euros

General Information

  Theme/Domain : Optimization, machine learning and statistical methods Biologie et santé, Sciences de la vie et de la terre (BAP A)

  Town/city : Gif sur Yvette

  Inria Center : CRI Saclay - Île-de-France

  Starting date : 2020-10-01

  Duration of contract : 3 months

  Deadline to apply : 2020-09-25Contacts

  Inria Team : PARIETAL

  Recruiter : Thirion Bertrand / Bertrand.Thirion@inria.fr

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